Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aws/tools-for-devops-agent --skill bedrock-adoption-readinessgit clone --depth 1 https://github.com/aws/tools-for-devops-agentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aws/tools-for-devops-agent/bedrock-adoption-readiness)<a href="https://agentmods.dev/skills/aws/tools-for-devops-agent/bedrock-adoption-readiness"><img src="https://agentmods.dev/badge/skills/aws/tools-for-devops-agent/bedrock-adoption-readiness.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00137 | $0.03424 |
| Opus 5 | $0.00068 | $0.01712 |
| Sonnet 5 | $0.00027 | $0.00685 |
| Haiku 4.5 | $0.00014 | $0.00342 |
Grade A, and why
bedrock-adoption-readiness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bedrock Adoption Readiness Assessment
Assess an AWS account's readiness to run Amazon Bedrock at production scale. Covers four dimensions: IAM governance, data retention (ZDR), quota and capacity headroom, and operational observability. Operates across both Standard Bedrock and Mantle (OpenAI models) surfaces.
Important: Two Surfaces
Bedrock operates across two control planes. Both must be assessed.
| Standard Bedrock | Mantle (OpenAI models) | |
|---|---|---|
| CloudWatch namespace | AWS/Bedrock |
AWS/BedrockMantle |
| Metric names | Invocations, InputTokenCount, OutputTokenCount |
Inferences, TotalInputTokens, TotalOutputTokens |
| CW dimensions | ModelId |
Model, Project |
| IAM prefix | bedrock:, bedrock-runtime: |
bedrock-mantle: |
| Cost discriminator | No marker in USAGE_TYPE | -mantle- substring in USAGE_TYPE |
| Cross-region inference | Yes - Geographic (us., eu., apac. prefixes) and Global (global. prefix) |
No (in-region only) |
When to Use
Activate this skill when the user asks to:
- Review or assess Bedrock production readiness
- Audit Bedrock IAM permissions or access governance
- Check Bedrock quota utilization or capacity planning
- Evaluate Zero Data Retention (ZDR) configuration
- Validate Bedrock operational monitoring setup
- Prepare for scaling Bedrock usage in production
Dimension States
Every dimension reports one of three states:
- ASSESSED: Data collected, rules applied, findings produced
- NOT_ASSESSED: Collection failed or data unreachable (state the reason)
- INSUFFICIENT_DATA: Data returned but volume too low for meaningful analysis
A dimension producing zero findings after successful collection = GOOD. A dimension producing zero findings because collection failed = NOT_ASSESSED. These must render differently.
Step 1: Identify Scope
Ask the user:
- Which AWS account to assess
- Which regions to review (if unknown, discover by listing metrics in us-east-1, us-east-2, us-west-2)
- Whether they have specific concerns or want a full assessment
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 313 lines · 137 tokens per session scan A 1f470f45d1ec
bedrock-adoption-readiness is a skill published in the GitHub repository aws/tools-for-devops-agent (45 stars, last pushed 4d ago), licensed Apache-2.0. It adds 137 tokens to every session and 3,424 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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